Remote Sensing, Geophysics, and Modeling to Support Precision Agriculture—Part 2: Irrigation Management
Arya Pradipta,
Pantelis Soupios,
Nektarios Kourgialas,
Maria Doula,
Zoi Dokou,
Mohammad Makkawi,
Mohammed Alfarhan,
Bassam Tawabini,
Panagiotis Kirmizakis,
Mohamed Yassin
Affiliations
Arya Pradipta
Department of Geosciences, College of Petroleum Engineering & Geosciences, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia
Pantelis Soupios
Department of Geosciences, College of Petroleum Engineering & Geosciences, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia
Nektarios Kourgialas
Lab. of Water Resources, Irrigation & Env. Geoinformatics, Institute of Olive Tree, Subtropical Plants and Viticulture, Hellenic Agricultural Organization (ELGO Dimitra), 73100 Chania, Greece
Maria Doula
Laboratory of Non-Parasitic Diseases, Benaki Phytopathological Institute, 14561 Athens, Greece
Zoi Dokou
Department of Civil and Environmental Engineering, California State University, Sacramento, CA 90032, USA
Mohammad Makkawi
Department of Geosciences, College of Petroleum Engineering & Geosciences, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia
Mohammed Alfarhan
Remote Sensing Lab, College of Petroleum Engineering & Geosciences, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia
Bassam Tawabini
Department of Geosciences, College of Petroleum Engineering & Geosciences, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia
Panagiotis Kirmizakis
Department of Geosciences, College of Petroleum Engineering & Geosciences, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia
Mohamed Yassin
Interdisciplinary Research Center for Membranes and Water Security, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia
Food and water security are considered the most critical issues globally due to the projected population growth placing pressure on agricultural systems. Because agricultural activity is known to be the largest consumer of freshwater, the unsustainable irrigation water use required by crops to grow might lead to rapid freshwater depletion. Precision agriculture has emerged as a feasible concept to maintain farm productivity while facing future problems such as climate change, freshwater depletion, and environmental degradation. Agriculture is regarded as a complex system due to the variability of soil, crops, topography, and climate, and its interconnection with water availability and scarcity. Therefore, understanding these variables’ spatial and temporal behavior is essential in order to support precision agriculture by implementing optimum irrigation water use. Nowadays, numerous cost- and time-effective methods have been highlighted and implemented in order to optimize on-farm productivity without threatening the quantity and quality of the environmental resources. Remote sensing can provide lateral distribution information for areas of interest from the regional scale to the farm scale, while geophysics can investigate non-invasively the sub-surface soil (vertically and laterally), mapping large spatial and temporal domains. Likewise, agro-hydrological modelling can overcome the insufficient on-farm physicochemical dataset which is spatially and temporally required for precision agriculture in the context of irrigation water scheduling.